DanLing
Introduction
DanLing (丹灵) is a high-level library to help with running neural networks flexibly and transparently.
DanLing is meant to be a scaffold for experienced researchers and engineers who know how to define a training loop, but are bored of writing the same boilerplate code, such as DDP, logging, checkpointing, etc., over and over again.
Therefore, DanLing does not feature complex Runner designs with many pre-defined methods and complicated hooks. Instead, the Runner of DanLing just initialise the essential parts for you, and you can do whatever you want, however you want.
Although many attributes and properties are pre-defined and are expected to be used in DanLing, you have full control over your code.
DanLing also provides some utilities, such as [NestedTensor][danling.NestedTensor], [LRScheduler][danling.optim.LRScheduler], [catch][danling.utils.catch], etc.
Installation
Install the most recent stable version on pypi:
pip install danling
Install the latest version from source:
pip install git+https://github.com/ZhiyuanChen/DanLing
It works the way it should have worked.
License
DanLing is multi-licensed under the following licenses:
- The Unlicense
- GNU Affero General Public License v3.0 or later
- GNU General Public License v2.0 or later
- BSD 4-Clause "Original" or "Old" License
- MIT License
- Apache License 2.0
You can choose any (one or more) of these licenses if you use this work.
SPDX-License-Identifier: Unlicense OR AGPL-3.0-or-later OR GPL-2.0-or-later OR BSD-4-Clause OR MIT OR Apache-2.0
1 maintainer
Metadata
1 maintainer
Release files for danling 0.4.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| danling-0.4.6.tar.gz | 7.0 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| danling-0.4.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.5 MB
Release files / danling-0.4.6.tar.gz
| Download URL | danling-0.4.6.tar.gz |
|---|---|
| Size | 7.0 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7083c0403bf2c2c653480b2d6b59d4fe9935d677b7e4aa9e98bb65549f467910
|
|
BLAKE2b-256 checksum How to use checksums |
773647e4cc09ea13f6fb9e92f44313133f283c0330a954629313b88c6920f365
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 6, 2026.
Transparency logRelease files / danling-0.4.6-py3-none-any.whl
| Download URL | danling-0.4.6-py3-none-any.whl |
|---|---|
| Size | 556.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
2de8edd226d5b4bda576a7ffc7f6b4ac094262a2fe54084ae39b95b3bf12890b
|
|
BLAKE2b-256 checksum How to use checksums |
5a769e9c0a8fa9c1e57711bfcd9ef46bd9a4e0b52d17c2f665f4683e4dae37f7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 6, 2026.
Transparency log
